From metal-poor to metal-rich: new insights on Milky Way bar, bulge and disc with machine learning and Gaia.
Machine Learning applications such as the hybrid-CNN (Guigluon et al. 2024) allows to homogeneously combine Gaia RVS spectra, photometry (G, BP, RP), parallaxes and the XP coefficients to obtain precise stellar parameters down to S/N=15. In this contribution, I will focus on the scientific applications and new results facilitated by this machine
Nepal, Samir et al.
Fecha de publicación:
7
2024